Understanding the Impact of Algorithmic Discrimination on Unethical Consumer Behavior DOI Creative Commons
Binbin Sun,

Shan Pei,

Qingjin Wang

et al.

Behavioral Sciences, Journal Year: 2025, Volume and Issue: 15(4), P. 494 - 494

Published: April 8, 2025

The prevalence of artificial intelligence (AI) increases social concern surrounding unethical consumer behavior in human–AI interaction. Existing research has mainly focused on anthropomorphic characteristics AI and (UCB). However, the role algorithms behavior, which is central to AI, not yet fully understood. Drawing exchange theory, this study investigates impact algorithmic discrimination UCB explores interrelationships underlying mechanisms. Through three experiments, found that experiencing significantly UCB, with anticipatory guilt mediating relationship. Moreover, consumers’ negative reciprocity beliefs moderated effects UCB. In addition, distinguish between active passive based their ethical motivations. This enhances study’s universality by assessing both types behaviors highlighting differences. These insights extend current within purview agents provide valuable into effectively mitigating losses caused behaviors, offering improved directions for facilitating fair, reliable, efficient interactions businesses consumers.

Language: Английский

Similarity-attraction theory perspective on service employees and service robots’ interactions DOI
Huijun Yang, Hanqun Song, Yao‐Chin Wang

et al.

Service Industries Journal, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 24

Published: April 3, 2025

Language: Английский

Citations

0
Understanding the Impact of Algorithmic Discrimination on Unethical Consumer Behavior DOI Creative Commons
Binbin Sun,

Shan Pei,

Qingjin Wang

et al.

Behavioral Sciences, Journal Year: 2025, Volume and Issue: 15(4), P. 494 - 494

Published: April 8, 2025

The prevalence of artificial intelligence (AI) increases social concern surrounding unethical consumer behavior in human–AI interaction. Existing research has mainly focused on anthropomorphic characteristics AI and (UCB). However, the role algorithms behavior, which is central to AI, not yet fully understood. Drawing exchange theory, this study investigates impact algorithmic discrimination UCB explores interrelationships underlying mechanisms. Through three experiments, found that experiencing significantly UCB, with anticipatory guilt mediating relationship. Moreover, consumers’ negative reciprocity beliefs moderated effects UCB. In addition, distinguish between active passive based their ethical motivations. This enhances study’s universality by assessing both types behaviors highlighting differences. These insights extend current within purview agents provide valuable into effectively mitigating losses caused behaviors, offering improved directions for facilitating fair, reliable, efficient interactions businesses consumers.

Language: Английский

Citations

0